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Robust distributed control within a curve virtual tube for a robotic swarm under self‐localization drift and precise relative navigation

Yan Gao, Chenggang Bai, Quan Quan

Year
2023
Citations
14

Abstract

Abstract To guide the movement of a robotic swarm in a corridor‐like environment, a curve virtual tube with no obstacle inside was designed in our previous work. This article generalizes the controller design to the condition that all robots have self‐localization drifts and precise relative navigation, where the flocking algorithm is introduced to reduce the negative impact of the self‐localization drift. Similar to the “many wrongs principle,” it is shown that the cohesion behavior and the velocity alignment behavior are able to reduce the influence of the position measurement drift and the velocity measurement error, respectively. For convenience in practical use, a modified vector field controller with five control terms is put forward. Finally, the effectiveness of the proposed method is validated by numerical simulations and real experiments.

Keywords

Control theory (sociology)Flocking (texture)Swarm behaviourComputer sciencePosition (finance)RobotObstacle avoidanceObstacleRelative velocityController (irrigation)

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